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Statistical Human Genetics

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Cover of 'Statistical Human Genetics'

Table of Contents

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    Book Overview
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    Chapter 1 Statistical Genetic Terminology
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    Chapter 2 Identification of Genotype Errors
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    Chapter 3 Detecting Pedigree Relationship Errors
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    Chapter 4 Identifying Cryptic Relationships
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    Chapter 5 Estimating Allele Frequencies
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    Chapter 6 Testing Departure from Hardy-Weinberg Proportions
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    Chapter 7 Estimating Disequilibrium Coefficients
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    Chapter 8 Detecting Familial Aggregation
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    Chapter 9 Estimating Heritability from Twin Studies
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    Chapter 10 Estimating Heritability from Nuclear Family and Pedigree Data
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    Chapter 11 Correcting for Ascertainment
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    Chapter 12 Segregation Analysis Using the Unified Model
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    Chapter 13 Design Considerations for Genetic Linkage and Association Studies
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    Chapter 14 Model-Based Linkage Analysis of a Quantitative Trait
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    Chapter 15 Model-Based Linkage Analysis of a Binary Trait
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    Chapter 16 Model-Free Linkage Analysis of a Quantitative Trait
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    Chapter 17 Model-Free Linkage Analysis of a Binary Trait
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    Chapter 18 Single Marker Association Analysis for Unrelated Samples
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    Chapter 19 Single Marker Family-Based Association Analysis Conditional on Parental Information
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    Chapter 20 Single Marker Family-Based Association Analysis Not Conditional on Parental Information
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    Chapter 21 Calibrating Population Stratification in Association Analysis
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    Chapter 22 Cross-Phenotype Association Analysis Using Summary Statistics from GWAS
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    Chapter 23 Haplotype Inference
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    Chapter 24 Multi-SNP Haplotype Analysis Methods for Association Analysis
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    Chapter 25 The Analysis of Ethnic Mixtures
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    Chapter 26 Detecting Multiethnic Rare Variants
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    Chapter 27 Identifying Gene Interaction Networks
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    Chapter 28 Structural Equation Modeling
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    Chapter 29 Mendelian Randomization
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    Chapter 30 Preprocessing and Quality Control for Whole-Genome Sequences from the Illumina HiSeq X Platform
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    Chapter 31 Processing and Analyzing Human Microbiome Data
Attention for Chapter 19: Single Marker Family-Based Association Analysis Conditional on Parental Information
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Chapter title
Single Marker Family-Based Association Analysis Conditional on Parental Information
Chapter number 19
Book title
Statistical Human Genetics
Published in
Methods in molecular biology, January 2017
DOI 10.1007/978-1-4939-7274-6_19
Pubmed ID
Book ISBNs
978-1-4939-7273-9, 978-1-4939-7274-6
Authors

Ren-Hua Chung, Daniel D. Kinnamon, Eden R. Martin

Abstract

Family-based designs have been commonly used in association studies. Different family structures such as extended pedigrees and nuclear families, including parent-offspring triads and families with multiple affected siblings (multiplex families), can be ascertained for family-based association analysis. Flexible association tests that can accommodate different family structures have been proposed. The pedigree disequilibrium test (PDT) (Martin et al., Am J Hum Genet 67:146-154, 2000) can use full genotype information from general (possibly extended) pedigrees with one or multiple affected siblings but requires parental genotypes or genotypes of unaffected siblings. On the other hand, the association in the presence of linkage (APL) test (Martin et al., Am J Hum Genet 73:1016-1026, 2003) is restricted to nuclear families with one or more affected siblings but can infer missing parental genotypes properly by accounting for identity-by-descent (IBD) parameters. Both the PDT and APL test are powerful association tests in the presence of linkage and can be used as complementary tools for association analysis. This chapter introduces these two tests and compares their properties. Recommendations and notes for performing the tests in practice are provided.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 25%
Researcher 1 25%
Student > Doctoral Student 1 25%
Unknown 1 25%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 1 25%
Agricultural and Biological Sciences 1 25%
Psychology 1 25%
Unknown 1 25%